{"paper":{"title":"Asymptotically Optimal Sequential Experimentation Under Generalized Ranking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Michael N. Katehakis, Wesley Cowan","submitted_at":"2015-10-07T17:52:30Z","abstract_excerpt":"We consider the \\mnk{classical} problem of a controller activating (or sampling) sequentially from a finite number of $N \\geq 2$ populations, specified by unknown distributions. Over some time horizon, at each time $n = 1, 2, \\ldots$, the controller wishes to select a population to sample, with the goal of sampling from a population that optimizes some \"score\" function of its distribution, e.g., maximizing the expected sum of outcomes or minimizing variability. We define a class of \\textit{Uniformly Fast (UF)} sampling policies and show, under mild regularity conditions, that there is an asymp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.02041","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}